AI & Human-Powered Moderation Tools to Safeguard Your Brand Reputation
Innodata combines the power of machine learning technology with the precision of highly trained subject matter experts to identify and classify inappropriate content. Our global network of skilled moderation specialists leverages best-in-class technology to ensure your brand is shielded from risky content, in every language.
Accuracy
By combining AI and manual tools to address your moderation needs, we aim to deliver the highest possible moderation accuracy and consistency.
Dedicated Workforce
We employ a highly skilled workforce – never crowdsourced - that understands how to identify questionable content according to your specifications.
Global Knowledge
Our team has deep domain experience in over 20 languages across the globe to assist you 24/7.
Deep Learning
Our content moderation platform is continually learning and adapting to recognize and monitor risky content in real-time for fast and scalable results.
Easy Integration
Innodata provides seamless integration into your desired workflow.
Talk with an Expert
Content moderation protects your brand and builds trust with your users. How can I help?

Sam Burr- Data Engineering Specialist
Sam helps clients develop strategies that enable them to manage, distribute and exploit the full potential of data using AI-based solutions. He is passionate about helping others unlock value from structured and unstructured data using ML & AI.
Content Moderation Services
Innodata provides content moderation services to address a broad range of challenges:
Explicit Language / Themes
Threatening Dialog
NSFW / Content Unfit for Minors
Suicidal Intents
Pornographic Images/Video
Content Moderation Success Stories
We help some of the world’s most valuable brands build trust and improve user experience.
Content Provider Navigates Risky Content
Company partners with Innodata to shield minors from consuming explicit content.
Content Provider Navigates Risky Content
Objective
- A leading global content platform faced challenges with the content in Japanese Manga comics.
- Most comics were categorized as suited for general consumption, but a substantial part of Manga comics featured explicit pornographic content and are unsuitable for consumption by children under 16. As such, they needed to classify the content.
Solution
- Innodata developed a documented system that was used to categorize the suitability of comics content for consumption by children.
- Over 70% of the content had to be recategorized.
- Innodata also worked with the client for building a metadata tagging methodology to create an improved search and content match suited for children.
Results
- The metadata tagging and re-categorization process helped curtail inadvertent access to pornographic content by children.
- The upfront inclusion of the metadata based on content, language and context led to a highly granular classification effort, avoiding the need for lengthy and costly publication reviews.
Government Agency Monitors Social Media for Suicide Intent
Agency needed data on suicide-related behaviors.
Government Agency Monitors Social Media for Suicide Intent
Objective
- A government agency in Canada needed an AI solution to accurately assess public opinion on the topic of suicide through the analysis of online social media feeds.
- The agency needed ongoing data on trends, as well as risk and protective factors associated with suicide-related behaviours among various population groups.
Solution
- Innodata leveraged its Agility Enterprise platform to monitor online social media platforms via keywords and location, and Innodata’s AI/ML-based Index.ml platform to auto-classify the data based on the suicide-related terms taxonomy.
- Monitoring included the following online social media platforms: Twitter, Facebook (public profile pages), YouTube (video comments only), and curated blogs.
Results
- The combination of the Agility Enterprise platform and the Index.ml platform enabled the acquisition of a comprehensive data set from online platforms and the accurate classification of the acquired data.
- The availability of indexed and classified online social media data enabled our SME analysts to prepare and deliver comprehensive findings and reports containing complete and accurate data for the agency’s consumption.
Online Gaming Platform Powers Down Inappropriate Content
Platform ensures chat logs are a safe haven for its virtual community.
Online Gaming Platform Powers Down Inappropriate Content
Objective
A leading online gaming platform needed help in reviewing vast amounts of chat logs – line-by-line - to determine if the content is appropriate for its all-ages audience.
Solution
- Innodata developed a chatbot to automatically read and identify inappropriate text.
- We built a vocabulary of inappropriate short phrases and idioms and applied the corresponding corrections to these phrases and idioms; double-checked by SMEs.
- Further enhancement to the solution involved the addition of ML to analyse the chat logs and automatically classify the text.
Results
- The automated process for review and correction of chat logs ensures content is age-appropriate.
- The addition of ML is expected to further improve the accuracy of flagging inappropriate content.
- The initial feed will teach ML to learn the language (similar to building the vocabulary), and then be supplemented by an SME for QA.